Refine
Year of publication
Document Type
- Doctoral Thesis (3157) (remove)
Language
- English (3157) (remove)
Keywords
- climate change (52)
- Klimawandel (51)
- Modellierung (27)
- Nanopartikel (22)
- machine learning (21)
- Blickbewegungen (17)
- Fernerkundung (17)
- Arabidopsis thaliana (16)
- Arktis (15)
- Synchronisation (15)
Institute
- Institut für Biochemie und Biologie (735)
- Institut für Physik und Astronomie (551)
- Institut für Geowissenschaften (407)
- Institut für Chemie (347)
- Extern (142)
- Institut für Informatik und Computational Science (128)
- Institut für Mathematik (124)
- Institut für Umweltwissenschaften und Geographie (117)
- Institut für Ernährungswissenschaft (114)
- Department Linguistik (97)
- Hasso-Plattner-Institut für Digital Engineering GmbH (91)
- Wirtschaftswissenschaften (86)
- Department Psychologie (71)
- Sozialwissenschaften (45)
- Hasso-Plattner-Institut für Digital Engineering gGmbH (42)
- Institut für Anglistik und Amerikanistik (38)
- Department Sport- und Gesundheitswissenschaften (31)
- Fachgruppe Politik- & Verwaltungswissenschaft (16)
- Fachgruppe Betriebswirtschaftslehre (15)
- Strukturbereich Kognitionswissenschaften (14)
- Philosophische Fakultät (13)
- Öffentliches Recht (11)
- Department Erziehungswissenschaft (10)
- Institut für Philosophie (9)
- Digital Engineering Fakultät (7)
- Fachgruppe Volkswirtschaftslehre (7)
- Institut für Germanistik (7)
- Potsdam Institute for Climate Impact Research (PIK) e. V. (7)
- Institut für Jüdische Studien und Religionswissenschaft (6)
- Institut für Künste und Medien (5)
- Mathematisch-Naturwissenschaftliche Fakultät (5)
- Fachgruppe Soziologie (3)
- Historisches Institut (3)
- Psycholinguistics and Neurolinguistics (3)
- Institut für Jüdische Theologie (2)
- Institut für Romanistik (2)
- Multilingualism (2)
- Patholinguistics/Neurocognition of Language (2)
- Applied Computational Linguistics (1)
- Bürgerliches Recht (1)
- Department Grundschulpädagogik (1)
- Fakultät für Gesundheitswissenschaften (1)
- Foundations of Computational Linguistics (1)
- Institut für Religionswissenschaft (1)
- Institut für Slavistik (1)
- Interdisziplinäres Zentrum für Dynamik komplexer Systeme (1)
- Interdisziplinäres Zentrum für Kognitive Studien (1)
- Lehreinheit für Wirtschafts-Arbeit-Technik (1)
- Phonology & Phonetics (1)
- Potsdam Research Institute for Multilingualism (PRIM) (1)
- Syntax, Morphology & Variability (1)
Electricity production contributes to a significant share of greenhouse gas emissions in Europe and is thus an important driver of climate change. To fulfil the Paris Agreement, the European Union (EU) needs a rapid transition to a fully decarbonised power production system. Presumably, such a system will be largely based on renewables. So far, many EU countries have supported a shift towards renewables such as solar and wind power using support schemes, but the economic and political context is changing. Renewables are now cheaper than ever before and have become cost-competitive with conventional technologies. Therefore, European policymakers are striving to better integrate renewables into a competitive market and to increase the cost-effectiveness of the expansion of renewables. The first step was to replace previous fixed-price schemes with competitive auctions. In a second step, these auctions have become more technology-open. Finally, some governments may phase out any support for renewables and fully expose them to the competitive power market.
However, such policy changes may be at odds with the need to rapidly expand renewables and meet national targets due to market characteristics and investors’ risk perception. Without support, price risks are higher, and it may be difficult to meet an investor’s income expectations. Furthermore, policy changes across different countries could have unexpected effects if power markets are interconnected and investors able to shift their investments. Finally, in multi-technology auctions, technologies may dominate, which can be a risk for long-term power system reliability. Therefore, in my thesis, I explore the effects of phasing out support policies for renewables, of coordinating these phase-outs across countries, and of using multi-technology designs. I expand the public policy literature about investment behaviour and policy design as well as policy change and coordination, and I further develop an agent-based model.
The main questions of my thesis are what the cost and deployment effects of gradually exposing renewables to market forces would be and how coordination between countries affects investors’ decisions and market prices.. In my three contributions to the academic literature, I use different methods and come to the following results. In the first contribution, I use a conjoint analysis and market simulation to evaluate the effects of phasing out support or reintroducing feed-in tariffs from the perspective of investors. I find that a phase-out leads to investment shifts, either to other still-supported technologies or to other countries that continue to offer support. I conclude that the coordination of policy changes avoids such shifts.. In the second contribution, I integrate the empirically-derived preferences from the first contribution in to an agent-based power system model of two countries to simulate the effects of ending auctions for renewables. I find that this slows the energy transition, and that cross-border effects are relevant. Consequently, continued support is necessary to meet the national renewables targets. In the third contribution, I analyse the outcome of past multi-technology auctions using descriptive statistics, regression analysis as well as case study comparisons. I find that the outcomes are skewed towards single technologies. This cannot be explained by individual design elements of the auctions, but rather results from context-specific and country-specific characteristics. Based on this, I discuss potential implications for long-term power system reliability.
The main conclusions of my thesis are that a complete phase-out of renewables support would slow down the energy transition and thus jeopardize climate targets, and that multi-technology auctions may pose a risk for some countries, especially those that cannot regulate an unbalanced power plant portfolio in the long term. If policymakers decide to continue supporting renewables, they may consider adopting technology-specific auctions to better steer their portfolio. In contrast, if policymakers still want to phase out support, they should coordinate these policy changes with other countries. Otherwise, overall transition costs can be higher, because investment decisions shift to still-supported but more expensive technologies.
Volcanic hydrothermal systems are an integral part of most volcanoes and typically involve a heat source, adequate fluid supply, and fracture or pore systems through which the fluids can circulate within the volcanic edifice. Associated with this are subtle but powerful processes that can significantly influence the evolution of volcanic activity or the stability of the near-surface volcanic system through mechanical weakening, permeability reduction, and sealing of the affected volcanic rock. These processes are well constrained for rock samples by laboratory analyses but are still difficult to extrapolate and evaluate at the scale of an entire volcano. Advances in unmanned aircraft systems (UAS), sensor technology, and photogrammetric processing routines now allow us to image volcanic surfaces at the centimeter scale and thus study volcanic hydrothermal systems in great detail. This thesis aims to explore the potential of UAS approaches for studying the structures, processes, and dynamics of volcanic hydrothermal systems but also to develop methodological approaches to uncover secondary information hidden in the data, capable of indicating spatiotemporal dynamics or potentially critical developments associated with hydrothermal alteration. To accomplish this, the thesis describes the investigation of two near-surface volcanic hydrothermal systems, the El Tatio geyser field in Chile and the fumarole field of La Fossa di Vulcano (Italy), both of which are among the best-studied sites of their kind. Through image analysis, statistical, and spatial analyses we have been able to provide the most detailed structural images of both study sites to date, with new insights into the driving forces of such systems but also revealing new potential controls, which are summarized in conceptual site-specific models. Furthermore, the thesis explores methodological remote sensing approaches to detect, classify and constrain hydrothermal alteration and surface degassing from UAS-derived data, evaluated them by mineralogical and chemical ground-truthing, and compares the alteration pattern with the present-day degassing activity. A significant contribution of the often neglected diffuse degassing activity to the total amount of degassing is revealed and constrains secondary processes and dynamics associated with hydrothermal alteration that lead to potentially critical developments like surface sealing. The results and methods used provide new approaches for alteration research, for the monitoring of degassing and alteration effects, and for thermal monitoring of fumarole fields, with the potential to be incorporated into volcano monitoring routines.
The remarkable antifouling properties of zwitterionic polymers in controlled environments are often counteracted by their delicate mechanical stability. In order to improve the mechanical stabilities of zwitterionic hydrogels, the effect of increased crosslinker densities was thus explored. In a first approach, terpolymers of zwitterionic monomer 3-[N -2(methacryloyloxy)ethyl-N,N-dimethyl]ammonio propane-1-sulfonate (SPE), hydrophobic monomer butyl methacrylate (BMA), and photo-crosslinker 2-(4-benzoylphenoxy)ethyl methacrylate (BPEMA) were synthesized. Thin hydrogel coatings of the copolymers were then produced and photo-crosslinked. Studies of the swollen hydrogel films showed that not only the mechanical stability but also, unexpectedly, the antifouling properties were improved by the presence of hydrophobic BMA units in the terpolymers.
Based on the positive results shown by the amphiphilic terpolymers and in order to further test the impact that hydrophobicity has on both the antifouling properties of zwitterionic hydrogels and on their mechanical stability, a new amphiphilic zwitterionic methacrylic monomer, 3-((2-(methacryloyloxy)hexyl)dimethylammonio)propane-1-sulfonate (M1), was synthesized in good yields in a multistep synthesis. Homopolymers of M1 were obtained by free-radical polymerization. Similarly, terpolymers of M1, zwitterionic monomer SPE, and photo-crosslinker BPEMA were synthesized by free-radical copolymerization and thoroughly characterized, including its solubilities in selected solvents.
Also, a new family of vinyl amide zwitterionic monomomers, namely 3-(dimethyl(2-(N -vinylacetamido)ethyl)ammonio)propane-1-sulfonate (M2), 4-(dimethyl(2-(N-vinylacetamido)ethyl)ammonio)butane-1-sulfonate (M3), and 3-(dimethyl(2-(N-vinylacetamido)ethyl)ammonio)propyl sulfate (M4), together with the new photo-crosslinker 4-benzoyl-N-vinylbenzamide (M5) that is well-suited for copolymerization with vinylamides, are introduced within the scope of the present work. The monomers are synthesized with good yields developing a multistep synthesis. Homopolymers of the new vinyl amide zwitterionic monomers are obtained by free-radical polymerization and thoroughly characterized. From the solubility tests, it is remarkable that the homopolymers produced are fully soluble in water, evidence of their high hydrophilicity. Copolymerization of the vinyl amide zwitterionic monomers, M2, M3, and M4 with the vinyl amide photo-crosslinker M5 proved to require very specific polymerization conditions. Nevertheless, copolymers were successfully obtained by free-radical copolymerization under appropriate conditions.
Moreover, in an attempt to mitigate the intrinsic hydrophobicity introduced in the copolymers by the photo-crosslinkers, and based on the proven affinity of quaternized diallylamines to copolymerize with vinyl amides, a new quaternized diallylamine sulfobetaine photo-crosslinker 3-(diallyl(2-(4-benzoylphenoxy)ethyl)ammonio)propane-1-sulfonate (M6) is synthesized. However, despite a priori promising copolymerization suitability, copolymerization with the vinyl amide zwitterionic monomers could not be achieved.
Light is the essential energy source for plants to drive photosynthesis. In nature, light availability is highly variable and often fluctuates on very short time scales. As a result, plants developed mechanisms to cope with these fluctuations. Understanding how to improve light use efficiency in natural fluctuating light (FL) conditions is a major target for agronomy.
In the first project, we identified an Arabidopsis thaliana plant that showed reduced levels of rapidly inducible non-photochemical quenching (NPQ). This plant was devoid of any T-DNA insertion. Using a mapping-by-sequencing approach, we successfully located the causal genomic region near the end of chromosome 4. Through variant investigations in that region, we identified a deletion of about 20 kb encompassing 9 genes. By complementation analysis, we confirmed that one of the deleted genes, VTC2, is the causal gene responsible for the low NPQ. Loss of VTC2 decreased NPQ particularly in old leaves, with young leaves being only slightly affected. Additionally, ascorbate levels were almost abolished in old leaves, likely causing the NPQ decrease by reducing the activity of the xanthophyll cycle. Although ascorbate levels in younger leaves were reduced compared to wild-type plants, they remained at a comparably higher level. This difference may be due to the VTC2 paralog VTC5, which is expressed at a higher level in young leaves than in old ones.
Plants require the PROTON GRADIENT REGULATION 5 (PGR5) protein for survival in FL. pgr5 mutants die because they fail to increase the luminal proton concentration in response to high light (HL) phases. A rapid elevation in ∆pH is needed to slow down electron transport through the Cytochrome b6 f complex (photosynthetic control). In FL, such lack of control in the pgr5 mutants results in photosystem I (PSI) overreduction, reactive oxygen species (ROS) production, and cell death. Decreases in photosystem II (PSII) activity introduced by crossing pgr5 with PSII deficient mutants
rescued the lethality of pgr5 in FL. PGR5 was suggested to act as part of the ferredoxin-plastoquinone reductase (FQR), involved in cyclic electron transfer around PSI. However, the proposed molecular role of PGR5 remains highly debated. To learn more about PGR5 function, we performed a forward genetic screen in Arabidopsis thaliana to identify EMS-induced suppressor mutants surviving longer when grown in FL compared to pgr5 mutants (referred to as ”suppressor of pgr5 lethality in fluctuating light”, splf ). 11 different candidate genes were identified in a total of 22 splf plants.
Mutants of seven of these genes in the pgr5 background showed low Fv/Fm values when grown in non-fluctuating low light (LL). Five of these 4genes were previously reported to have a role in PSII biogenesis or function. Two others, RPH1 and a DEAD/DEAH box helicase (AT3G02060), have not been linked to PSII function before. Three of splf candidate genes link to primary metabolism, fructose-2,6-bisphosphatase (F2KP ), udp-glucose pyrophosphorylase 1 (UGP1 ) and ferredoxin-dependent glutamate synthase (Fd-GOGAT ). They are characterized by the fact that they survive longer in FL than pgr5 mutants but do not procede beyond the early vegetative
phase and then die.
Classification, prediction and evaluation of graph neural networks on online social media platforms
(2024)
The vast amount of data generated on social media platforms have made them a valuable source of information for businesses, governments and researchers. Social media data can provide insights into user behavior, preferences, and opinions. In this work, we address two important challenges in social media analytics. Predicting user engagement with online content has become a critical task for content creators to increase user engagement and reach larger audiences. Traditional user engagement prediction approaches rely solely on features derived from the user and content. However, a new class of deep learning methods based on graphs captures not only the content features but also the graph structure of social media networks.
This thesis proposes a novel Graph Neural Network (GNN) approach to predict user interaction with tweets. The proposed approach combines the features of users, tweets and their engagement graphs. The tweet text features are extracted using pre-trained embeddings from language models, and a GNN layer is used to embed the user in a vector space. The GNN model then combines the features and graph structure to predict user engagement. The proposed approach achieves an accuracy value of 94.22% in classifying user interactions, including likes, retweets, replies, and quotes.
Another major challenge in social media analysis is detecting and classifying social bot accounts. Social bots are automated accounts used to manipulate public opinion by spreading misinformation or generating fake interactions. Detecting social bots is critical to prevent their negative impact on public opinion and trust in social media. In this thesis, we classify social bots on Twitter by applying Graph Neural Networks. The proposed approach uses a combination of both the features of a node and an aggregation of the features of a node’s neighborhood to classify social bot accounts. Our final results indicate a 6% improvement in the area under the curve score in the final predictions through the utilization of GNN.
Overall, our work highlights the importance of social media data and the potential of new methods such as GNNs to predict user engagement and detect social bots. These methods have important implications for improving the quality and reliability of information on social media platforms and mitigating the negative impact of social bots on public opinion and discourse.
The icosahedral non-hydrostatic large eddy model (ICON-LEM) was applied around the drift track of the Multidisciplinary Observatory Study of the Arctic (MOSAiC) in 2019 and 2020. The model was set up with horizontal grid-scales between 100m and 800m on areas with radii of 17.5km and 140 km. At its lateral boundaries, the model was driven by analysis data from the German Weather Service (DWD), downscaled by ICON in limited area mode (ICON-LAM) with horizontal grid-scale of 3 km.
The aim of this thesis was the investigation of the atmospheric boundary layer near the surface in the central Arctic during polar winter with a high-resolution mesoscale model. The default settings in ICON-LEM prevent the model from representing the exchange processes in the Arctic boundary layer in accordance to the MOSAiC observations. The implemented sea-ice scheme in ICON does not include a snow layer on sea-ice, which causes a too slow response of the sea-ice surface temperature to atmospheric changes. To allow the sea-ice surface to respond faster to changes in the atmosphere, the implemented sea-ice parameterization in ICON was extended with an adapted heat capacity term.
The adapted sea-ice parameterization resulted in better agreement with the MOSAiC observations. However, the sea-ice surface temperature in the model is generally lower than observed due to biases in the downwelling long-wave radiation and the lack of complex surface structures, like leads. The large eddy resolving turbulence closure yielded a better representation of the lower boundary layer under strongly stable stratification than the non-eddy-resolving turbulence closure. Furthermore, the integration of leads into the sea-ice surface reduced the overestimation of the sensible heat flux for different weather conditions.
The results of this work help to better understand boundary layer processes in the central Arctic during the polar night. High-resolving mesoscale simulations are able to represent temporally and spatially small interactions and help to further develop parameterizations also for the application in regional and global models.
Plant metabolism serves as the primary mechanism for converting assimilated carbon into essential compounds crucial for plant growth and ultimately, crop yield. This renders it a focal point of research with significant implications. Despite notable strides in comprehending the genetic principles underpinning metabolism and yield, there remains a dearth of knowledge regarding the genetic factors responsible for trait variation under varying environmental conditions. Given the burgeoning global population and the advancing challenges posed by climate change, unraveling the intricacies of metabolic and yield responses to water scarcity became increasingly important in safeguarding food security.
Our research group has recently started to work on the genetic resources of legume species. To this end, the study presented here investigates the metabolic diversity across five different legume species at a tissue level, identifying species-specific biosynthesis of alkaloids as well as iso-/flavonoids with diverse functional groups, namely prenylation, phenylacylation as well as methoxylation, to create a resource for follow up studies investigation the metabolic diversity in natural diverse populations of legume species.
Following this, the second study investigates the genetic architecture of drought-induced changes in a global common bean population. Here, a plethora of quantitative trait loci (QTL) associated with various traits are identified by performing genome-wide association studies (GWAS), including for lipid signaling. On this site, overexpression of candidates highlighted the induction of several oxylipins reported to be pivotal in coping with harsh environmental conditions such as water scarcity.
Diverging from the common bean and GWAS, the following study focuses on identifying drought-related QTL in tomato using a bi-parental breeding population. This descriptive study highlights novel multi-omic QTL, including metabolism, photosynthesis as well as fruit setting, some of which are uniquely assigned under drought. Compared to conventional approaches using the bi-parental IL population, the study presented improves the resolution by assessing further backcrossed ILs, named sub-ILs.
In the final study, a photosynthetic gene, namely a PetM subunit of the cytochrome b6f complex encoding gene, involved in electron flow is characterized in an horticultural important crop. While several advances have been made in model organisms, this study highlights the transition of this fundamental knowledge to horticultural important crops, such as tomato, and investigates its function under differing light conditions. Overall, the presented thesis combines different strategies in unveiling the genetic components in multi-omic traits under drought using conventional breeding populations as well as a diverse global population. To this end, it allows a comparison of either approach and highlights their strengths and weaknesses.
With Arctic ground as a huge and temperature-sensitive carbon reservoir, maintaining low ground temperatures and frozen conditions to prevent further carbon emissions that contrib-ute to global climate warming is a key element in humankind’s fight to maintain habitable con-ditions on earth. Former studies showed that during the late Pleistocene, Arctic ground condi-tions were generally colder and more stable as the result of an ecosystem dominated by large herbivorous mammals and vast extents of graminoid vegetation – the mammoth steppe. Characterised by high plant productivity (grassland) and low ground insulation due to animal-caused compression and removal of snow, this ecosystem enabled deep permafrost aggrad-ation. Now, with tundra and shrub vegetation common in the terrestrial Arctic, these effects are not in place anymore. However, it appears to be possible to recreate this ecosystem local-ly by artificially increasing animal numbers, and hence keep Arctic ground cold to reduce or-ganic matter decomposition and carbon release into the atmosphere.
By measuring thaw depth, total organic carbon and total nitrogen content, stable carbon iso-tope ratio, radiocarbon age, n-alkane and alcohol characteristics and assessing dominant vegetation types along grazing intensity transects in two contrasting Arctic areas, it was found that recreating conditions locally, similar to the mammoth steppe, seems to be possible. For permafrost-affected soil, it was shown that intensive grazing in direct comparison to non-grazed areas reduces active layer depth and leads to higher TOC contents in the active layer soil. For soil only frozen on top in winter, an increase of TOC with grazing intensity could not be found, most likely because of confounding factors such as vertical water and carbon movement, which is not possible with an impermeable layer in permafrost. In both areas, high animal activity led to a vegetation transformation towards species-poor graminoid-dominated landscapes with less shrubs. Lipid biomarker analysis revealed that, even though the available organic material is different between the study areas, in both permafrost-affected and sea-sonally frozen soils the organic material in sites affected by high animal activity was less de-composed than under less intensive grazing pressure. In conclusion, high animal activity af-fects decomposition processes in Arctic soils and the ground thermal regime, visible from reduced active layer depth in permafrost areas. Therefore, grazing management might be utilised to locally stabilise permafrost and reduce Arctic carbon emissions in the future, but is likely not scalable to the entire permafrost region.
Organic-inorganic hybrids based on P3HT and mesoporous silicon for thermoelectric applications
(2024)
This thesis presents a comprehensive study on synthesis, structure and thermoelectric transport properties of organic-inorganic hybrids based on P3HT and porous silicon. The effect of embedding polymer in silicon pores on the electrical and thermal transport is studied. Morphological studies confirm successful polymer infiltration and diffusion doping with roughly 50% of the pore space occupied by conjugated polymer. Synchrotron diffraction experiments reveal no specific ordering of the polymer inside the pores. P3HT-pSi hybrids show improved electrical transport by five orders of magnitude compared to porous silicon and power factor values comparable or exceeding other P3HT-inorganic hybrids. The analysis suggests different transport mechanisms in both materials. In pSi, the transport mechanism relates to a Meyer-Neldel compansation rule. The analysis of hybrids' data using the power law in Kang-Snyder model suggests that a doped polymer mainly provides charge carriers to the pSi matrix, similar to the behavior of a doped semiconductor. Heavily suppressed thermal transport in porous silicon is treated with a modified Landauer/Lundstrom model and effective medium theories, which reveal that pSi agrees well with the Kirkpatrick model with a 68% percolation threshold. Thermal conductivities of hybrids show an increase compared to the empty pSi but the overall thermoelectric figure of merit ZT of P3HT-pSi hybrid exceeds both pSi and P3HT as well as bulk Si.